Intelligent lighting management and building control system

ABSTRACT

A method of controlling and managing a plurality of system managers, a plurality of lights and devices, including human interfaces and building automation devices is disclosed. The method includes a system manager collecting data from the plurality of lights and devices. The system manager uses the collected data to determine an adjacency of lights and devices. The system manager dynamically places the plurality of lights and devices into zones and binding human interface devices to the zones, and a dynamically configures the devices to control the zones. The devices perform self-calibration and self-commissioning. The system manager and devices perform ongoing calibration and commissioning. The system manager and devices operate resiliently in case of failure of the system manager, other devices, or software or hardware failures in the devices. The system manager and the devices operate on the collected data to determine usage patterns, and to efficiently manage the plurality of lights and devices.

INTRODUCTION

Solid State Lighting is the third revolution in illumination, after theinvention of fire and electricity-based lighting. Buildings oftenoperate inefficiently today; energy and lighting management lacksgranular control of devices to allow for efficient management.

The existing approaches to managing lighting are all enhancements to thesecond-wave, electrically-based lighting, where typically each lightfixture, sensor and human interface device is independently powered atbuilding voltage levels, occasionally at low voltage. State of the artLight Management Systems (LMS) allow centralized management of singlelights or groups of lights through software, with hardware controlstypically located at each sensor or switch used to control light levelsdirectly, or through the LMS.

The emergence of low-power, high intensity LEDs, semi-conductors, forgeneral illumination, combined with IP networking paradigms, makespractical a novel Lighting Management System to achieve granular controlof lighting and thereby realize substantial energy savings.

This same Management System, which consists of control elementsinstalled in building plenums or above ceilings, can be used tosimultaneously control and power a variety of systems, sensors anddevices, including those used for light sensing, day-lighting andscreening control, HVAC, security, emergency, surveillance, buildingaccess and building and environmental control. This list of sensors anddevices is for illustrative purposes and not meant to be exhaustive.

We refer to this combined system as a Building Control System, or BCS.

DESCRIPTION OF EMBODIMENTS

The described embodiments provide methods for powering, controlling andoptimally managing solid state lighting (SSL) for energy and costefficiencies, and for human comfort and productivity, and providemethods for controlling luminaires and devices, including sensors, in abuilding, and provide methods for managing and controlling sensordevices and utilizing the sensor input to control and manage otherdevices, including those used for lighting, HVAC, security, emergency,surveillance, building access and building and environmental control.

One method includes an appliance, described as a Control Engine, or CE,that centrally powers and manages SSL luminaires, sensors and otherdevices. In one embodiment, the Control Engine connects to the buildingelectrical system, either directly wired or through a socket, anddistributes low voltage to power each luminaire and each device. Thedevices are connected to, powered and controlled by this Control Engine,typically connected by wire, for example Power-Over-Ethernet, or POE.Numerous Control Engines can be connected over Ethernet/IP to form alight management or building control system, or BCS. Another element inthe LMS or BCS is a central management system, or CMS, to manage thenetwork of Control Engines and connected devices.

The BCS manages all devices and sensors from the Control Engines, basedon policies installed by the CMS. The CEs form peer relationships toshare relevant sensor and device data in order to execute a variety ofalgorithms, including discovery of luminaires, sensors and devices;luminaire, device and sensor topology and adjacencies, CE adjacencies,binding of human interface devices to luminaires and zones, calibration,configuration; light management, including daylight harvesting, task,scene and emergency lighting and demand response management.

The BCS provides a high level of granular control by including a rangeof low cost sensors or devices in each luminaire or other device,including light, temperature, occupancy, monitoring and video sensors ordevices. Luminaires in this and typical topologies are mounted in theceiling, often one every 40 to a 100 square feet. By including sensorsin each luminaire or device, it and other devices can be controlledindividually, and the BCS has visibility and control over an entirebuilding floor. Motion and occupancy sensors are typically expensive andoften deployed in rooms or zones, controlling multiple lights. Byincluding low-cost sensors in each luminaire, the BCS can provideindividual luminaire control.

The system is illustrated in FIG. 1:

A Software Based System for Lighting Control

This patent application describes an embodiment of a BCS for the realtime control and management of the lighting infrastructure of buildingswith a view to optimizing the use of electrical power and to providingmore visibility into power consumption.

The proposed system consists of three major architectural abstractionsrespectively named the device layer, the enforcement layer and themanagement layer.

The device layer consists of sensors that can report relevant metrics(for example ambient light levels, temperature gauges, motion detectors,occupancy sensors and other relevant aspects of the environment) as wellas lighting devices such as solid state LEDs, fluorescent light fixturesetc. The power required by luminaires for light elements, such ashigh-illumination LEDs, as well as for running embedded microcontrollersis assumed to be provided by components of the enforcement layerdescribed below. In a preferred embodiment, the sensors and lightelements will be packaged inside a single luminaire device. This will ata minimum include sensors for sensors for measuring ambient light andtemperature and for detection of motion or human presence, together withan LED light element.

The enforcement layer is responsible for gathering measurements andapplying sophisticated software algorithms in order to compute thedesired levels of illumination and the power to be applied to lightingdevices in order to achieve these levels. In a preferred embodiment thislayer would be implemented as one or more software systems (hencereferred to as Control Engines or CEs) consisting of a CPU complex, anoperating system and additional software as needed to perform itsfunction. It will contain dedicated power supplies and circuitry (forexample IEEE 802.3 compliant Ethernet wiring to carry data and power)for obtaining measurements from sensors and for supplying power tolighting devices. This circuitry may optionally include an AC-to-DCconversion facility for powering luminaires if needed.

The management layer is responsible for management of the system. In apreferred embodiment it will consist of a workstation (henceforthreferred to as a Central Management System or CMS) consisting of one ormore CPUs and an operating system together with additional software.This software will discover components of the system as they arecommissioned, organize them into groupings, obtain user preferences andmodify software algorithms accordingly. It will monitor the functioningof the system and report findings to system administrators. Thisreporting includes a system map, statistical data, alarms, system logsand reminders to users. The control layer will also be designed toaccept requests to reduce power consumption (such as for example frompublic utility companies in times of power shortages) and modify powerlevels being supplied to light devices appropriately.

The components of the different layers will exchange information (e.g.measurements, configuration settings, operating state information,requests for statistics and responses to such requests) usingproprietary data formats.

The FIG. 2 illustrates the entire system described above in schematicform.

The lines connecting the different entities represent cabling pathsalong which data and power travels among them. For example, the sensors(represented by small circles) in the device layer receive commands andreport measurements to the CEs. Light devices in the device layer(similarly represented by circles) receive power from the CEs alongthese connections. Connections among the CEs represent pathways alongwhich they share data such as policy, measurements and system topology.The lines connecting the Central Management System to the CEs representsdata flow such as configurations and command/response sequences. As thediagram suggests, the entire system has a hierarchical structure whereeach entity aggregates and represents the entities below it to its peersand to other external entities.

Theory of Operation

Each CE detects sensors and lighting devices directly connected to itusing a data protocol (to be described elsewhere.) Using proprietaryalgorithms described later in this specification, the CEscollaboratively deduce the spatial topology of the light devices andsensors. These spatial aggregations (referred to as ‘lighting zones’)are then reported to the Central Management System where a properlyauthorized user may (by logging in e.g. using a web browser or a similartool) examine the topology or manually alter it or associate usageattributes to it. The user may at any time enter or alter policies suchas daytime working hours, optimum light levels desired during day andnight times and other parameters relevant to system operation.

The CEs can then monitor ambient light levels, the time of day andbuilding occupancy to calculate the appropriate amount of power to besupplied to the lighting devices so as to maintain desired levels ofillumination. In doing this they will in general need to share datarelevant to the algorithm that decides the amount of power supplied todifferent devices. Additionally the Central Management System willexpose an external data interface using which a duly authorized externaluser (e.g. a power utility company) may communicate indications ofpotential power shortages. The system may choose to respond by reducingits power usage—possibly at the cost of reduced lighting, airconditioning or powering down other devices.

Fault Tolerance and Recovery

Another aspect of the system is a multiplicity of measures designed toincrease resiliency of operation in the event of malfunctioningcomponents. We now describe some of these measures.

One possible source of failures is the software running inside the CEs.Software is known to be subject to logical ‘bugs’ which can result inendless loops or deadlock conditions during which no useful work isperformed and the software remains ‘stuck’. This could result in thesystem becoming unresponsive to changing conditions or attempts toaccess it from the Central Management System. The system thereforeproposes ‘watchdog timers’ in the CEs. These are so designed as toautomatically restart the CE (e.g. by rebooting it) to a knownresponsive state in the event of these timers expiring. During normalhealthy operating conditions it is the responsibility of the software toreset the timer periodically and prevent it from expiring.

A related failure condition can occur if for a variety of reasons thepower supply subsystem stops receiving commands from the CE. If thishappens for a specified period of time, the subsystem (normallycollocated inside the CE but operating autonomously) is designed tocontinue providing power at some pre-specified level. This level couldeither be the last level as requested by the CE or a predetermined fixedthreshold. The Central Management System could program either one ofthese preferences at the start of operations. This allows a ‘headless’(less responsive) form of operation in case of a breakdown of thecommunication between the CE software and the power subsystem.

Failures at the sensor or lighting device layer must be guarded againstby overprovisioning redundant sensors and devices.

Failures of the connectivity links between the different system entitiesmust similarly be guarded against by overprovisioning measures commonlyknown in networking.

Manual Override

An aspect of the system is the ability to manually override theautomatic operation of the CEs with an external switch that puts thepower supply subsystem in a mode whereby preset levels of power aresupplied to the lighting and other devices and the CE's dynamic powersupply algorithms are overridden. Although this has the externalappearance of a light switch, in reality this is a user interface deviceto send a binary ‘force on/off’ command to the power subsystem that willcontrol the operation of this mode. This feature may be used to preventan outage in case of a system malfunction.

Clustering

Some existing lighting control solutions require that lighting devicesin an area that must be controlled as a collection must be connected toand controlled by a single controller. This places restrictions on thenumber of such lighting devices as well as the topology of connections.Our solution lifts these restrictions by allowing the lighting devicesunder consideration to be connected to any one of multiple CEs. Theaspect of our solution that makes this possible is called ‘clustering’i.e. sharing of configuration and state information among multiple CEswhereby the relevant algorithms run in a distributed manner amongmultiple CPUs. Thus, for instance, all the lighting devices in a singlelarge conference room need not be connected to and controlled by asingle CE but may be distributed among multiple CEs. The CEs will sharethe measurements reported by different sensors so that the samealgorithm may simultaneously run in all of them and power to eachlighting device may be controlled by the CE connected to it.

The CEs form peer relationships to share relevant sensor and device datain order to execute a variety of algorithms, including discovery ofluminaires, sensors and devices; luminaire, device and sensor topologyand adjacencies, CE adjacencies, binding of human interface devices toluminaires and zones, calibration, configuration; light management,including daylight harvesting, task, scene and emergency lighting anddemand response management.

Another aspect of clustering is that if one of the CEs in a clusterfails then the affected conference area can still be serviced by theremaining members of the cluster avoiding a single point of failure.Since many of the luminaires will be driven at much less than full power(50-70%), luminaires near one that fails can be driven at higher powerand light levels.

FIG. 3 illustrates how clustering may be used to distribute the controlof lights in an area across multiple cooperating CEs.

Commissioning

An embodiment of the BCS includes methods to ensure that the entiresystem is plug and play. CEs will detect each attached device and learnthe identity of the device. CEs will also share peer information witheach other, and will detect adjacent CEs and their attached devices,ensuring complete topology independence. Some of the methods are used todetermine adjacencies and topologies; this is achieved thru sensors thatadaptively sense adjacencies based on device output, including lightfrom luminaires and temperature levels from HVAC devices.

Upon installation, a CE will discover other CEs by running a CEdiscovery algorithm and sending IP messages to discover other CEsattached to the building network. The algorithm allows CEs to alsoverify connectivity and adjacency thru the use of lights. A new CE, upondetecting other CEs, will negotiate for a time-slot to turn on alllights, allowing other CEs to detect the new CE through their lightsensors.

After completing the CE discovery algorithm, the CE will negotiate for atime slot to run a device adjacency algorithm. In the case ofluminaires, the testing CE will turn on each luminaire serially to allowit and other CEs to use their sensors to detect proximity to the litluminaire. In one method, the testing CE will use a protocol to announcethe device to be tested to other CEs, then solicit response back fromCEs that detect adjacent light. The light levels are used to detect andmeasure proximity; therefore the algorithm is best run in darkness. Thealgorithm will allow adjacent devices in a zone as well asinterconnected rooms to be detected, and allow the CMS to collectadjacency and build a composite map. Similar algorithms can be used withHVAC equipment.

HID devices, including light switches and touch-panels, also participatein these discovery algorithms. These HID devices can also includesensors to determine adjacencies and topology. One embodiment is theconcept of a dynamic soft-switch, with dimmable properties, that can bedynamically bound to lights or zones. The soft-switch can be presentedon a touch-panel, or on a computer. In one embodiment, multiplesoft-switches can be dynamically instantiated in a touch-panel, based onthe number of zones needed or dynamically created.

Another property of soft-switches is that unlike conventional lightswitches of various forms, the proposed HID devices can be bound—thoughsoftware—to specific lights or groups of lights, called zones. Anexample might be to associate one or a bank of switches with groups oflights. This binding can be performed manually, or determined by the CEduring the discovery process.

An example is the discovery of luminaires above an open floor area in afactory, or populated with cubicles. HID devices can be deployed atentry points to the open area. The installer can include sufficientswitches to control each area, or install a touch panel to control theentire floor area. Another embodiment is n-way soft-switches; thesoft-binding of HIDs connected to CEs eliminates the need for physicaln-way switches, and the cost associate with the switches themselves andthe wiring of the these switches. An embodiment of the BCS bindsswitches to zones, allowing switches at each entryway to control aspecific luminaire, a zone, or all luminaires.

All CEs within a cluster will negotiate with other CEs to run thesediscovery algorithms, at installation, when a topology change isdetected and periodically to confirm adjacency.

Once discovered and zoned, devices need to be calibrated.

Calibration and Manual Commissioning

An embodiment of the system includes the methods used for both manualand automated calibration and commissioning. Calibration here refers tomeasuring the relationship between power settings applied to each deviceand the corresponding measurements recorded on all the sensors. Themethods apply to calibration of devices, and the effect of these devicesin the building.

Device calibration of luminaires includes measuring lumen output perdevice, lumen efficiency at the desktop, where sensors close to the tasksurface detect the efficiency of individual and zone luminaires.Calibration can also be performed manually with light measuring devices.

During the self-commissioning process, the system self-calibrates. Eachdevice is tested independently, and measured using internal andsurrounding sensors. The system then calibrates devices operatingtogether, and again the devices are measured by internal and surroundingsensors. Self calibration is performed periodically, often unobtrusivelywhile the system is fully functional.

The system is also designed to optimize manual calibration. Existingtechniques to calibrate light sensors, for example, are painstaking andexpensive, often requiring manual tweaking of set-points/screws on thesensor itself while on a ladder and in a position that affects thebehavior of the sensor. The calibrator must hop on and off a ladder toget the correct results, and then perform this for every sensor sincethe control logic is in the sensor itself.

In the described embodiment, the system self-commissions where possible,but in some cases manual commissioning is desirable and required. Allsensor control logic is centralized in the CE, and correlated with othersensors around it to achieve system level calibration, not individualsensors.

The envisioned system is will support integration with manualcalibration devices, and includes full support for role-based workflowsthat can be setup at the CMS, then downloaded to the calibration device,for example a PDA. Sensor readings will be immediately communicated fromthe device to the system in one of a variety of mechanisms, includingwirelessly and thru the use of light pulses between devices and sensors.

The following embodiments are described:

-   -   The calibration of a single luminaire is measured by multiple        sensors (on the device itself and at surrounding devices) and        applied to other luminaires in the rest of the system. The        system calibrates each luminaire, then settles on a system lumen        output set by default or policy.    -   The calibration and subsequent settings of each device in a zone        and adjacent zones is measured to calibrate the system as a        whole. Devices are then adjusted manually or dynamically to        comply with policy settings to achieve the system settings        required.    -   The manual calibration of the output of a single luminaire, for        example measured at a desktop surface, can be used to calibrate        other luminaires in that zone or connected zones. Adjacent        devices in the system can be dynamically, sequentially        calibrated, and then the entire system can be calibrated based        on consistency/deviation from the calibrated device.    -   All luminaires in an adjacent zone can be commissioned to        conform to the settings of a single luminaire in that zone by        adjusting all devices to conform with the behavior of the        calibrated and commissioned device.    -   All communication between manual calibration or commissioning        devices and the system is fully automated, based on system        workflows. The workflows are designed to minimize user input,        and control tasks in a calibration, commissioning or        troubleshooting workflow.    -   Zone bindings of devices are typically automated, but can be        executed or adjusted thru manual commissioning. The devices in        the entire zone can be confirmed—thru flashing lights—to        conclude calibration or zoning workflows, or modified by        adding/removing luminaires from the zone by selecting them from        the PDA by location and/or light pulse.    -   A commissioning or calibration workflow may include confirming,        correcting or identifying device addresses and locations, for        example the location and occupancy associated with a particular        luminaire.    -   The workflows of binding or associating the occupant associated        with one or more luminaires can be downloaded to a PDA, and use        light levels to confirm the location of the PDA and the location        itself. The workflow will coordinate successive locations by        flashing lights at the next location.    -   Devices may dynamically override calibrated or commissioned        settings based on user preference.

Centralized Algorithms for Lighting Control

Policies entered at the time of commissioning are to be combined withsensor readings at operating time to come up with multiple strategies(algorithms) for controlling power output to lighting devices. Thesealgorithms optimize light levels for efficiency, security, comfort,safety and other factors.

These algorithms may depend on the nature of the area to be lit (e.g.whether it is an individual work area, a common work area, a hallway, anindividual office, a conference room, a restroom etc.) Additionally, thecontrol algorithm may also take into account specific activities (e.g. ameeting or a presentation), tasks or ‘scenes’. Depending on the contextdifferent algorithms may be deployed for lighting control. These couldoperate independently or in combination.

An embodiment of the CEs utilizes sensor input from multiple, directlyattached or remote devices to control different individual devices. Onemethod is to measure occupancy, motion, temperature and ambient lightlevels from multiple sensors and use this data to set light levels orcontrol other devices, including HVAC controllers. A building that isfully occupied is managed differently from one that is lightly occupied.Light and environmental controls will adapt based on occupancy; the CEsdetect occupancy and set light levels, heat or air-conditioning toappropriate levels, including levels selected by the individual oridentified occupants, either manually or adaptively learned fromhistorical preferences. The control algorithms reconcile occupancy,identity, user preferences, time of day and system capabilities withpreset policies for comfort, safety, efficiency or cost, includingluminaire and LED lifetime, energy efficiency and light levels. Thisincludes the control of multiple luminaires to achieve the besttradeoffs of cost, efficiency and light level—each luminaire isadaptively calibrated for efficiency, performance and lumen output—andadjacent luminaires are controlled based on preset policies. The controlalgorithms detect ambient light levels near windows and will raise ordim light based on occupancy, preference and policies. These samealgorithms will detect a single occupant in a building at night, andadjust light levels and other building systems, including environmentaland security controls; this includes lighting the occupied andsurrounding areas appropriately, and task lighting when the occupantmoves, including lighting appropriate to the occupant's activity,including lighting hallways and different room types as the user movesaround the building.

Another method is to use this combined sensor data to detect usage andmotion patterns. Another method is to use this sensor data to adaptivelylearn how various rooms and types of rooms are used. One method includesperforming algorithms centrally, rather than at a device, to correlatethe data from multiple devices to achieve optimal effectiveness acrossmultiple devices. An example is the management of energy in a building,where daylighting and cooling tradeoffs are calculated to optimizeenergy savings by selecting whether to close blinds and turn lights up,or open the blinds and turn on air-conditioning.

The following algorithms are further embodiments:

-   -   A target light sensor reading or readings is established at the        time of initial commissioning. At the time of operation the        current light readings are compared with the target sensor        reading at a predetermined frequency (e.g. once every five        seconds) and depending on the aggregate difference the power        supplied to light devices is incremented or decremented. The        aggregate difference between current sensor readings and the        target readings may be obtained as the sum of squares or of        absolute values of the differences.    -   The current time is compared against values established at the        time of initial commissioning to decide if it is a scheduled        work time. If yes, normal operating logic is used. If not, an        altered target reading is used. This way light is not wasted        during scheduled non-work time (e.g. nights, holidays etc.)    -   Occupancy/motion sensors are used to infer physical occupancy.        If the area under question is occupied, normal operating logic        is used. If not, an alternative minimum power level is used to        avoid wasting power to light unoccupied areas.    -   In certain areas such as restrooms, stock rooms, wiring closets        which are occupied only occasionally, lights are powered off at        all times except when occupancy sensors indicate human presence.    -   Occupancy and motion sensing is typically performed using        ultrasonic or passive infrared detectors; these have limitations        and will often not detect an occupant who does not move for long        periods of time. An embodiment of the LMS/BCS uses low-cost        cameras, similar to the video cameras in laptops or digital        cameras, in each device, including luminaires, to obtain a        picture of the floor below. The CEs combine sensor data for the        cameras and other sensors to build a complete view of the floor,        and are able to detect even minor changes in the digital image.        This enhances the ability of the BCS to detect changes in motion        or occupancy to the pixel level. The CEs combine data from        multiple sensors centrally, and share this data between CEs to        create comprehensive images of the building floor; note that        this is a figurative term, since the image is three-dimensional.        The CMS uploads these images, and shares this realtime view,        creating a combined image for each building floor, affording        full control and visual imagery of the building.        Role Based Policy management

The Central Management System configures policies that govern theoperation of the CEs and determines system behavior. It also providesinformation about a system in use. This requires various human agents tointeract with the Central Management System to define, alter and managepolicies and request reports. These agents may have differing roles. Forexample, a wiring technician will interact with the system at set uptime establish the spatial relationships between the differentcomponents of the system. An IT administrator may need to interact withthe Central Management System and CEs to incorporate them into thecorporate networking infrastructure. Individual users may wish to log into control settings of individual areas. Facility managers may need toset up workplace power policies.

Clearly different users will need to have different levels of access tothe Central Management System so that they can perform theirresponsibilities without interfering with the work of others. Thisbrings up the need for a role based management capability. In oneembodiment, the Central Management System will separate out and clubtogether sets of operations (i.e. ‘roles’) and based on credentialspresented by a user at the time of logging in will enable or restrictthe user interface accordingly.

Lifecycle Management

An embodiment of the BCS performs algorithms to calibrate and maximizethe lifetime of the LEDs on a luminaire, and the luminaire itself, basedon luminaire temperature, voltage, current and light output. Thealgorithm will also increase current to the LEDs as they degrade overtime to ensure consistent light output levels.

Direct Current or DC

An embodiment of the CE can be powered by direct current, DC, eitherfrom a battery or directly from a solar electric distributiongrid/system. The BCS may be simultaneously connected to battery, solarand building electric grids, and enforce policies defined in the CMS tomanage power utilization to optimize for energy efficiency, includingutilizing solar power to drive the CE and its devices, and chargebatteries.

The CE will provide battery backup power to the DC grid, to power otherCEs as required.

The CE can also deliver DC power to the desktop, directly from itsattached DC grid.

Demand Response

An embodiment of the BCS performs algorithms to implement a variety ofcentrally controlled lighting policies, including demand responsealgorithms. During peak demand lighting and air-conditioning eachconsume 30% of a buildings energy footprint. Therefore, energyutilization in a building can be adjusted based on demand responsepolicies, including progressive dimming of light levels and reducedcooling, alternately based on occupancy, and can include adjustments fornormal occupancy or optimized occupancy. The CMS will also calculateoptimal consolidated occupancy patterns, allowing occupants tocongregate efficiently in spaces that are easier to cool. Integrationwith IT or other building systems can notify occupants to congregate,and power down unused computers and systems. These policies can bepreset, or can be enabled manually from a CMS. A single mouse click orcommand from a Public Utility can dim all lights in a campus by 15%,delay charging of battery backups, switch all power consumption to solarDC, and reduce cooling by increase building temperatures by a degree ortwo.

Task, Scene and Emergency Lighting Heuristics

An embodiment of the BCS implements lighting management algorithms fortask, scene and emergency lighting, as well as algorithms for adaptivelearning of lighting patterns. Task lighting algorithms includeintegration with calendar systems and using flashing lights to remindemployees that they are late for meetings, based on office or cubicleoccupancy or security badge identification. Scene lighting algorithmsinclude lighting scenes for specific individuals and their tasks,including lighting for a janitor working to a sequence of locations tobe cleaned, including light levels around the current location, andflashing lights at the next location, where these lights stop flashingonce the location is occupied the janitor. The sequence can beadaptively learned based on prior, observed workflows, or can bepre-programmed and include flashing lights to set task pace. Similarly,a task can include lighting for security guards making rounds in abuilding, where the path can be preset and turned on or off based onprogress, with light levels dimming down behind the guard, andintensifying in front of the guard's progress.

Scene lighting algorithms can include conference rooms lights that dimwhen the BCS detects that projector is turned on, and turn on when theprojector is turned off. Scene lighting can also be controlled by policyrules, including occupancy, time of day and demand response. One exampleis the use of light to turn on a bathroom's lights; when unoccupied, thebathroom is dark. When the door opens, sensors will detect a change inlight and occupancy, and turn on the bathroom lights to a present scenewhich may be to light only the parts of the bathroom where urinals andvanities are located. If the occupant moves towards a stall, the lightsover the stall, possibly adjacent one or all stalls will turn on.

Another embodiment is the use of active training or learning of occupantpatterns to optimize control of lights. In the bathroom example above,the system will observe movement, including the rate of movement, todetermine how lights should be controlled. For example, if an occupanthesitates before moving into the toilet stall area when it is dark, thesystem may turn the stall lights up to a certain level to eliminate thehesitation (for whatever reason—darkness, discomfort). Training can beoptimized even further to track behavior and preferences of individualsperforming different tasks. Examples include tracking an office orcubicle occupant to a particular location and learning his preferencesfor that location, or using his normal preferences to prelight thescene. Individuals can be recognized based on primary locations ofoccupancy, or identified thru security badges.

Scene lighting can also include security policies, including flashinglights when an occupancy or time off day policy is violated.

Emergency lighting algorithms include flashing lights when an emergencyis detected, announcing the emergency over speakers, lighting thepathways to emergency exits, including in sequence towards the exit,based on occupancy and location, mapping building occupancy for securitypersonnel, detecting heat, smoke and other environmental anomalies,including gunfire sound patterns, connecting to emergency respondersystems, and powering down non-emergency systems.

An embodiment of the system is its ability to profile users andbuildings and create usage footprints, and to use this input to generateoccupancy optimizations, including those for energy efficiency.

Specific WS Applications

The LMS/BCS supports algorithms for specific applications, includinghotels, schools, hospitals, retail, office-buildings, industrial,parking garages and residential. The CMS is programmed to identify thetype of building, and set/manage appropriate policies.

Different buildings have completely different needs. In a hotel,detection of room occupancy (thru keys or physical occupancy), can turnall lighting and environmental systems on/off. In existing parkinggarages, all lights are typically on; with the BCS, light can be used tocontrol occupancy, consolidating cars at the most efficient floors, forefficient ventilation, lighting and access.

Retail is driven by light levels; studies prove a high correlationbetween brightness and sales, so existing retail stores keep all lightsfully on, whether a section of the store is occupied or not. Efficientlight policies will keep traffic areas lit, showcase certain areas, anddim aisles with no occupants, then raise their lights when a shopperpasses or enters the aisle.

Schools and other academic institution have very specific and periodicoccupancy patterns, as well as very special security requirements. Allbuilding systems can be trained to learn the usage patterns of thebuildings. The BCS can also detect and identify known and unknown users,including anomalous occupancy patterns. The BCS can respond toemergencies in specific ways, including locking down classrooms whenemergencies or gunshots are detected by the system.

The latest building regulations for residences require occupancydetection in bathrooms, but not in the rest of the house. Residences areheated and cooled, but only large, expensive houses have zones. The BCScan optimize all residential systems, including heating and cooling, todeliver this where needed.

An Example System Embodiment

A system architecture for a Light Management System (LMS), including anarchitecture for Solid State Lights, consisting of sensors, luminaireand facility infrastructure devices, CEs and CMSes that monitor andcontrol the environment as described.

A system architecture for, and methods for managing, a Building ControlSystem (BCS), comprising, but not limited to:

-   -   A network of Control Engines, that power and control a number of        connected devices, including SSL luminaires, sensors, Human        Interface Devices and other devices.    -   Centralized Management Systems that manage a number of Control        Engines    -   Solid State Light luminaires, including embedded sensors or        other devices.    -   Sensors, including, but not limited to, ambient light,        temperature, voltage, current, occupancy, motion, air quality        sensors.    -   Human Interface Devices, including switches, touch panels,        commissioning and calibration devices    -   Building Infrastructure Control devices, including HVAC        controllers    -   Surveillance devices    -   Emergency devices, including emergency lighting, smoke detectors

The BCS embodiment comprises a common appliance to centrally power,control and manage a large number of low voltage devices, including SSLluminaires and sensors, described as a Control Engine (CE), where thenumber of devices is limited by the delivered power capacity of theappliance.

Each luminaire, device or sensor is powered by, controlled by andconnected to the Control Engine. The Control Engines are powered by AC,DC battery backups, or a DC grid that is optionally powered by solarphoto-electric devices. The CEs form clusters to share configuration andstate information and implement the environment control algorithms in adistributed fashion.

The Control Engine incorporates a headless mode of operation in whichpower is conveyed to devices without active control from the CE in theevent of CE failure other than the power sub-system. In this mode, aconnected HID device sends a signal to force the CE to power itsattached devices on or off. A HID device may force the entire cluster ofCEs to power on or off.

The embodiment includes methods of clustering comprising a method of CEdiscovery to identify connected CEs, a method of topology discoveryperformed by the CEs (as described above) to identify the topology ofadjacent luminaires, sensors and HIDs, by relying on the use of light tosense adjacent luminaires and a method of zoning performed by thecluster of CEs to group adjacent luminaires into zones.

This zoning embodiment further comprises a method of dynamic or manuallogical binding of HID devices to zones, unconstrained by physicaltopology. This includes the binding of multiple HID devices (or asoftware embodiment of a switch or dimmer on a HID) to a zone, eachperforming the function of a single N-way switch or dimmer. A HID devicemay be a physical switch or dimmer, or a touch-panel, PDA or computer,containing a software embodiment of a switch or dimmer deployedindividually or multiply on the HID.

Each CE performs centralized algorithms to centrally process sensor datafrom individual sensors, either local or remote. The CEs performcentralized control of individual devices based on input from multiple,adjacent sensors. Sensors on each luminaire or other device performoccupancy sensing, including video cameras utilized to obtain videoimagery of the room below. The occupancy sensing data can be used tocontrol SSL lighting and other devices based on efficiency, occupancy,lifetime, security, productivity, individual preference, andpsychological comfort tradeoffs.

The embodiment includes methods for self-commissioning and calibrationthat allow SSL luminaires to be plug and play at installation. A furtheroptimization is automated commissioning, including a method for thepropagation of calibration of a single device, including luminaires, toall adjacent, equivalent devices. Other embodiments comprise methods ofmanual commissioning and calibration, including optimized workflows, asdescribed above.

The embodiment includes methods of power efficiency management of theentire BCS, including luminaires and HVAC, including the calculation ofoptimal power use between different devices or BCS systems, thecalculation of optimal occupancy to achieve BCS system-wideefficiencies, demand response, loss of AC power, emergencies and policy.

The embodiment includes methods for identification of emergencies,including detection of smoke or other environmental factors, the soundof gunshots or unidentified occupants. During emergencies, theembodiment further comprising methods for device management duringemergencies, including use of lights and other devices to announce oralert occupants to emergencies, use of lights to directionallyilluminate emergency pathways, use of control devices to lockdown areas,use of occupancy sensing to track and identify occupants.

The embodiment includes heuristics and system training of occupant usageand preference, tasks and scenes, and facility (rooms, hallways, etc)usage and profiling, the illumination and dimming of light duringexecution of tasks, the use of lights to set task pace. This includesthe integration with office systems and occupancy detection andidentification; including to track individuals, to flash lights whenmeeting attendees are late for meetings and to illuminate meeting roomsprior to scheduled events.

1. A method of controlling and managing a plurality of system managers,a plurality of lights and devices, including human interfaces andbuilding automation devices; comprising: a system manager collectingdata from the plurality of lights and devices, the system manager usingthe collected data to determine an adjacency of lights and devices; thesystem manager dynamically placing the plurality of lights and devicesinto zones and binding human interface devices to the zones, and adynamic configuration of the devices to control the zones; the devicesperforming self-calibration and self-commissioning; the system managerand devices performing ongoing calibration and commissioning; the systemmanager and devices operating resiliently in case of failure of thesystem manager, other devices, or software or hardware failures in thedevices; the system manager and the devices operating on the collecteddata to determine usage patterns, and to efficiently manage theplurality of lights and devices.